語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Simulation and synthesis in medical ...
~
(1998 :)
Simulation and synthesis in medical imaging6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Simulation and synthesis in medical imagingedited by David Svoboda ... [et al.].
其他題名:
6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
其他題名:
SASHIMI 2021
其他作者:
Svoboda, David.
團體作者:
出版者:
Cham :Springer International Publishing :2021.
面頁冊數:
x, 154 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Diagnostic imagingCongresses.Digital techniques
電子資源:
https://doi.org/10.1007/978-3-030-87592-3
ISBN:
9783030875923$q(electronic bk.)
Simulation and synthesis in medical imaging6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
Simulation and synthesis in medical imaging
6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /[electronic resource] :SASHIMI 2021edited by David Svoboda ... [et al.]. - Cham :Springer International Publishing :2021. - x, 154 p. :ill., digital ;24 cm. - Lecture notes in computer science,129650302-9743 ;. - Lecture notes in computer science ;4891..
Method-Oriented Papers -- Detail matters: high-frequency content for realistic synthetic brain MRI generation -- Joint Image and Label Self-Super-Resolution -- Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset -- A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms -- Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images -- Learning-based Template Synthesis For Groupwise Image Registration -- The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties -- Transfer Learning in Optical Microscopy -- X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration -- Application-Oriented Papers -- Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks -- SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image -- Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging -- Cine-MRI simulation to evaluate tumor tracking -- GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.
This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation. *The workshop was held virtually.
ISBN: 9783030875923$q(electronic bk.)
Standard No.: 10.1007/978-3-030-87592-3doiSubjects--Topical Terms:
445235
Diagnostic imaging
--Digital techniques--Congresses.
LC Class. No.: RC78.7.D53 / S56 2021
Dewey Class. No.: 616.0754
Simulation and synthesis in medical imaging6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
LDR
:03378nmm a2200385 a 4500
001
609381
003
DE-He213
005
20210919203210.0
006
m d
007
cr nn 008maaau
008
220222s2021 sz s 0 eng d
020
$a
9783030875923$q(electronic bk.)
020
$a
9783030875916$q(paper)
024
7
$a
10.1007/978-3-030-87592-3
$2
doi
035
$a
978-3-030-87592-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
RC78.7.D53
$b
S56 2021
072
7
$a
UYT
$2
bicssc
072
7
$a
COM012000
$2
bisacsh
072
7
$a
UYT
$2
thema
072
7
$a
UYQV
$2
thema
082
0 4
$a
616.0754
$2
23
090
$a
RC78.7.D53
$b
S252 2021
111
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
245
1 0
$a
Simulation and synthesis in medical imaging
$h
[electronic resource] :
$b
6th International Workshop, SASHIMI 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
$c
edited by David Svoboda ... [et al.].
246
3
$a
SASHIMI 2021
246
3
$a
MICCAI 2021
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
x, 154 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Lecture notes in computer science,
$x
0302-9743 ;
$v
12965
490
1
$a
Image processing, computer vision, pattern recognition, and graphics
505
0
$a
Method-Oriented Papers -- Detail matters: high-frequency content for realistic synthetic brain MRI generation -- Joint Image and Label Self-Super-Resolution -- Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset -- A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms -- Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images -- Learning-based Template Synthesis For Groupwise Image Registration -- The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties -- Transfer Learning in Optical Microscopy -- X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration -- Application-Oriented Papers -- Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks -- SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image -- Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging -- Cine-MRI simulation to evaluate tumor tracking -- GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.
520
$a
This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation. *The workshop was held virtually.
650
0
$a
Diagnostic imaging
$x
Digital techniques
$v
Congresses.
$3
445235
650
0
$a
Diagnostic imaging
$x
Data processing
$v
Congresses.
$3
445765
650
1 4
$a
Image Processing and Computer Vision.
$3
274051
650
2 4
$a
Artificial Intelligence.
$3
212515
650
2 4
$a
Pattern Recognition.
$3
273706
650
2 4
$a
Computational Biology/Bioinformatics.
$3
274833
700
1
$a
Svoboda, David.
$3
853550
710
2
$a
SpringerLink (Online service)
$3
273601
711
2
$n
(3rd :
$d
1998 :
$c
Amsterdam, Netherlands)
$3
194767
773
0
$t
Springer Nature eBook
830
0
$a
Lecture notes in computer science ;
$v
4891.
$3
383229
830
0
$a
Image processing, computer vision, pattern recognition, and graphics.
$3
823073
856
4 0
$u
https://doi.org/10.1007/978-3-030-87592-3
950
$a
Computer Science (SpringerNature-11645)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000205962
電子館藏
1圖書
電子書
EB RC78.7.D53 S252 2021 2021
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
https://doi.org/10.1007/978-3-030-87592-3
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入